Sold by: ParaTools Inc.
Deployed on AWS
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This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack using AWS ParallelCluster, with over 100 HPC and AI/ML tools, a remote desktop environment (DCV), and cluster configuration built using the Spack package manager and a proprietary MVAPICH MPI tuned for AWS Elastic Fabric Adapter (EFA). It is a platform for developing AI/ML applications using tools such as TensorFlow, PyTorch, JAX, Keras, and Horovod tuned for AWS ParallelCluster, with a complete HPC software stack including numerical libraries (such as WRF, PETSc, Trilinos, SuperLU-dist), visualization tools (such as ParaView and VisIt), performance evaluation tools (such as TAU and HPCToolkit), HPC applications (such as LAMMPS, Xyce, CP2K, deal.II, GROMACS and Quantum Espresso).
Overview
ParaTools Pro for E4S™ - the Extreme-scale Scientific Software Stack, E4S™ hardened for commercial clouds and supported by ParaTools, Inc. provides a platform for developing and deploying HPC and AI/ML applications. It features a performant remote desktop environment (based on DCV) on the login node and compute nodes interconnected by a low-latency, high bandwidth network adapter based on AWS Elastic Fabric Adapter (EFA). ParaTools Pro for E4S™ features a suite of over 100 HPC tools built using the Spack package manager and a proprietary MVAPICH MPI tuned for EFA. It features ready to use HPC applications (such as World Research and Forecasting Model-WRF, LAMMPS, Xyce, CP2K, deal.II, GROMACS, Quantum Espresso) as well as AI/ML tools based on Python (such as TensorFlow, PyTorch, JAX, Horovod, Keras, OpenCV, matplotlib and supports Jupyter notebooks) and the Codium IDE. New packages can be easily installed using Spack and pip and are accessible on the cluster compute and login nodes. It may be used for developing the next generation of generative AI applications using a suite of Python tools and interfaces.
E4S™ has built a unified computing environment for deployment of open-source projects. E4S™ was originally developed to provide a common software environment for the exascale leadership computing systems currently being deployed at DOE National Laboratories across the U.S. Support for ParaTools Pro for E4S™ is available through ParaTools, Inc. This product has additional charges associated with it for optional product support and updates.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Office of Advanced Scientific Computing and Research (ASCR), under SBIR Award Number DE-SC0022502 ("E4S: Extreme-Scale Scientific Software Stack for Commercial Clouds").
Note: This product contains repackaged and tuned open source software (e.g., E4S™, Spack and AI/ML tools like Horovod, JAX, Keras etc.) which is configured and linked against a proprietary MVAPICH MPI implementation tuned for EFA.
The full list of E4S applications installed via Spack is as follows:
- adios2
- adios
- alquimia
- aml
- amrex
- arborx
- argobots
- ascent
- axom
- boost
- bricks
- butterflypack
- cabana
- caliper
- chai
- chapel
- charliecloud
- conduit
- cp2k
- cusz
- darshan-runtime
- darshan-util
- datatransferkit
- dealii
- dyninst
- e4s-alc
- e4s-cl
- ecp-data-vis-sdk
- exago
- exaworks
- faodel
- fftx
- flecsi
- flit
- flux-core
- fortrilinos
- fpm
- gasnet
- ginkgo
- globalarrays
- glvis
- gmp
- gotcha
- gptune
- gromacs
- h5bench
- hdf5-vol-async
- hdf5-vol-cache
- hdf5-vol-log
- hdf5
- heffte
- hpctoolkit
- hpx
- hypre
- kokkos-kernels
- kokkos
- laghos
- lammps
- lbann
- legion
- libcatalyst
- libnrm
- libquo
- libunwind
- loki
- mercury
- metall
- mfem
- mgard
- mpark-variant
- mpifileutils
- nccmp
- nco
- nek5000
- nekbone
- netcdf-fortran
- netlib-scalapack
- nrm
- nwchem
- omega-h
- openmpi
- papi
- papyrus
- parallel-netcdf
- paraview
- parsec
- pdt
- petsc
- phist
- plasma
- plumed
- precice
- pruners-ninja
- pumi
- py-cinemasci
- py-h5py
- py-jupyterhub
- py-libensemble
- py-petsc4py
- qthreads
- quantum-espresso
- raja
- rempi
- scr
- slate
- slepc
- stc
- strumpack
- sundials
- superlu-dist
- superlu
- swig
- sz3
- sz
- tasmanian
- tau
- trilinos
- turbine
- umap
- umpire
- unifyfs
- upcxx
- veloc
- visit
- vtk-m
- wannier90
- wps
- wrf
- xyce
- zfp
Highlights
- ParaTools Pro for E4S™ and Machine Learning stacks built and optimized for AWS EFA and ParallelCluster
- A proprietary MVAPICH MPI implementation that offers lower latency and higher throughput than default OpenMPI implementations for pre-installed applications and user installed applications
- HPC software environment managed using the Spack package manager
Details
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Delivery method
Delivery option
64-bit (Arm) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Any additional refund enquiries can be sent to support@paratools.com and will be considered individually on a case by case basis.
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Delivery details
64-bit (Arm) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
- AWS ParallelCluster compatibility: pcluster v3.13.2
- E4S release: 25.06
- Inter-node communication requirement: EFA compatible instances
- Default MPI: MVAPICH-4 Plus
- OS: Ubuntu 22.04
CRITICAL:
- Some versions prior to v2024.05.16.1904-pcluster-3.9.1-e4s-24.05-amd64 are exposed to the Log4Shell (CVE-2021-44228) vulnerability. (Vulnerable log4js versions were getting pulled in as a dependency of hive.) Please upgrade as soon as possible to this version or a version equal to or newer than v2024.05.16.1748-pcluster-3.11.0-e4s-24.05-arm64 to mitigate this vulnerability.
IMPORTANT:
- To use this product with AWS ParallelCluster, you must use the same version of parallel cluster, v3.13.2
- As of v2025.08.19.1250-pcluster-3.13.2-e4s-25.06-amd64, thanks to the adoption of MVAPICH-4 Plus, EFA enabled nodes are no longer required for multinode support. However, EFA enabled nodes are still recommended to acheive the best performance. To get a list of instance types that are EFA compatible you can use the AWS CLI:
aws ec2 describe-instance-types --filters Name=network-info.efa-supported,Values=true \
--query InstanceTypes[*].[InstanceType] \
--output text | sort
- This AWS Parallel Cluster ARM version of ParaTools Pro for E4S (TM) is now based on Ubuntu 22.04 and uses the ubuntu username for login.
Updates in this version:
- Improvements to VLLM environment
- Improvements to MPI environment for more seamless use of MVAPICH 4
- Improvements to default NodeJS environment
- Addition of packages to support development on Google C
- Google ADK
- Google Cloud CLI
- Updated Spack packages for:
- E4S CL v1.0.3
- E4S ALC v1.0.5
- Addition of new Python packages:
- Streamlit
- Kaggle
- Polars
- Django
- DSI Workflow
- Addition of new NodeJS packages:
- NPX
ParaTools Pro for E4S (TM) provides a turn-key cloud HPC solution with the E4S Software stack and machine learning tools and SDKs installed and optimized to run on AWS. The key software features and versions installed are:
- Ubuntu 22.04, ARM64
- DCV remote access installed
- Codium IDE
- Kubernetes
- NVIDIA Fabric Manager
- Libfabric
- LibEFA
- MVAPICH-4 Plus
- CUDA 12.8.1
- CUDA 11.8.0
- E4S 25.06 CPU applications installed
- World Research and Forecasting Model (WRF)
- NVIDIA NeMo (TM) bare-metal install v2.3.1
- BioNeMo
- VLLM
- Python/Machine learning tools, SDKs, Frameworks etc.
- TensorFlow, PyTorch, JAX, Horovod, Keras, OpenCV, OpenAI, Scikit-Learn
- numpy, scipy, matplotlib, pandas, opencv-python
- jupyter notebook
- pywaggle
The full list of E4S applications installed via Spack is as follows:
-- linux-ubuntu22.04-aarch64 / gcc@11.4.0 --------------
- adios2@2.10.2
- adios@1.13.1
- alquimia@1.1.0
- aml@0.2.1
- amrex@25.03
- arborx@1.5
- arborx@1.7
- argobots@1.2
- axom@0.10.1
- boost@1.79.0
- bricks@2023.08.25
- butterflypack@3.2.0
- cabana@0.7.0
- caliper@2.12.1
- chai@2024.07.0
- chapel@2.4.0
- charliecloud@0.38
- conduit@0.9.3
- cp2k@2025.1
- cusz@0.14.0
- datatransferkit@3.1.1
- dealii@9.6.2
- dyninst@13.0.0
- e4s-alc@1.0.5
- e4s-cl@1.0.3
- exago@1.6.0
- exaworks@0.1.0
- fftx@1.2.0
- flecsi@2.3.2
- flit@2.1.0
- flux-core@0.67.0
- fortrilinos@2.3.0
- fpm@0.10.0
- gasnet@2025.2.0-snapshot
- ginkgo@1.9.0
- globalarrays@5.8.2
- glvis@4.2
- gmp@6.3.0
- gotcha@1.0.7
- gptune@4.0.0
- gromacs@2024.4
- h5bench@1.4
- hdf5-vol-async@1.7
- hdf5-vol-cache@v1.1
- hdf5-vol-log@1.4.0
- heffte@2.4.1
- hpctoolkit@2024.01.1
- hpx@1.10.0
- hypre@2.32.0
- kokkos-kernels@4.6.01
- kokkos@4.6.01
- laghos@3.1
- lammps@20240829.1
- lbann@0.104
- legion@24.12.0
- libceed@0.12.0
- libnrm@0.1.0
- libquo@1.4
- libunwind@1.8.1
- loki@0.1.7
- magma@2.9.0
- metall@0.30
- mfem@4.7.0
- mgard@2023-12-09
- mpark-variant@1.4.0
- mpifileutils@0.12
- nccmp@1.9.1.0
- nco@5.3.2
- nek5000@19.0
- nekbone@17.0
- netcdf-fortran@4.6.1
- netlib-lapack@3.12.1
- netlib-scalapack@2.2.2
- nrm@0.1.0
- nwchem@7.2.3
- omega-h@10.8.6-scorec
- openfoam@2412
- openmpi@5.0.6
- openpmd-api@0.16.1
- papi@7.1.0
- papyrus@1.0.2
- paraview@5.13.2
- parsec@3.0.2209
- pdt@3.25.2
- petsc@3.22.4
- phist@1.12.1
- plasma@24.8.7
- plumed@2.9.2
- precice@3.1.2
- pruners-ninja@1.0.1
- pumi@2.2.9
- py-h5py@3.12.1
- py-jupyterhub@1.4.1
- py-libensemble@1.4.3
- py-petsc4py@3.22.4
- qthreads@1.18
- quantum-espresso@7.4.1
- raja@2024.07.0
- rempi@1.1.0
- scr@3.1.0
- slate@2024.10.29
- slepc@3.22.2
- stc@0.9.0
- strumpack@8.0.0
- sundials@7.2.1
- superlu-dist@9.1.0
- superlu@7.0.0
- swig@4.0.2-fortran
- sz3@3.2.0
- tasmanian@8.1
- tau@2.34.1
- trilinos@16.1.0
- turbine@1.3.0
- umap@2.1.1
- umpire@2024.07.0
- upcxx@2023.9.0
- variorum@0.8.0
- vtk-m@2.2.0
- wannier90@3.1.0
- warpx@25.03
- wps@4.5
- wrf@4.6.1
- xyce@7.8.0
- zfp@1.0.0
Additional details
Usage instructions
The 1-Click Security Group opens port 22 only so that you can access your instance via SSH using login 'ubuntu', you may change this later.
For software development and basic usage:
- Launch the ParaTools Pro for E4S (TM) AMI via 1-Click
- On the 'EC2 Launch an Instance' page pick the key pair you will use to login
- On the 'EC2 Launch an Instance' page optionally edit the network settings by pressing the edit button. Adjust the firewall rules if needed to ensure ssh access and enable Auto-assign public IP if you plan to access the instance remotely from a non-AWS IP address.
- Click 'Launch Instance'
- Find your running instance in the EC2 Instances section of the EC2 dashboard, and connect to the instance via SSH using the key pair you previously selected by picking the instance and pressing the connect button.
For more advanced usage, including launching an ParaTools Pro for E4S (TM) cluster with AWS ParallelCluster, please see:
Resources
Support
Vendor support
For general support questions, please email support@paratools.com
Paid support contracts and custom AMIs and computing environments are available. Please see https://paratoolspro.com/ for additional details.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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